AIMC Topic: Meat

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Nondestructive freshness recognition of chicken breast meat based on deep learning.

Scientific reports
Identifying chicken breast freshness is an important component of poultry food safety. Traditional methods for chicken breast freshness recognition suffer from issues such as high cost, difficulty in recognition, and low efficiency. In this study, th...

Assessment of POPs in foods from western China: Machine learning insights into risk and contamination drivers.

Environment international
Persistent organic pollutants (POPs), including PCDD/Fs, PCBs, and PBDEs, are major environmental and food safety concerns due to their bioaccumulative and toxic properties. However, comprehensive research on the concentrations and influencing factor...

Estimation of irradiation doses in chicken samples using a reaction-based fingerprinting method.

Food chemistry
Food irradiation on an industrial scale calls for the development of rapid and inexpensive methods for the dose estimation after irradiation. An emerging solution to this problem is a reaction-based optical sensing strategy that is based on monitorin...

Tracking nutritional and quality changes in frozen pork: A 12-month study using 7 categories of meat parameters and VIS/NIR spectroscopy.

Food chemistry
Frozen pork stocks are critical for stabilizing food security and prices, but assessing nutritional and physicochemical changes during freezing remains challenging. This study conducted a 12-month frozen storage experiment at -20 °C on 50 pigs' longi...

Improving traceability and quality control in the red-meat industry through computer vision-driven physical meat feature tracking.

Food chemistry
Current traceability systems rely heavily on external markers which can be altered or tampered with. We hypothesized that the unique intramuscular fat patterns in beef cuts could serve as natural physical identifiers for traceability, while simultane...

Deep Learning Model Compression and Hardware Acceleration for High-Performance Foreign Material Detection on Poultry Meat Using NIR Hyperspectral Imaging.

Sensors (Basel, Switzerland)
Ensuring the safety and quality of poultry products requires efficient detection and removal of foreign materials during processing. Hyperspectral imaging (HSI) offers a non-invasive mechanism to capture detailed spatial and spectral information, ena...

Monitoring of veterinary drug residues in mutton based on hyperspectral combined with explainable AI: A case study of OFX.

Food chemistry
Veterinary drug residues in meat seriously harm human health. Rapid and accurate detection of veterinary drug residues is necessary to minimize contamination. Taking ofloxacin (OFX) residues in mutton as an example, the near-infrared hyperspectral im...

Machine Vision with a CMOS-Based Hyperspectral Imaging Sensor Enables Sensing Meat Freshness.

ACS sensors
Imaging spectral information of materials and analysis of its properties have become an intriguing tool for consumer electronics used for food inspection, beauty care, etc. Those sensory physical quantities are difficult to quantify. Hyperspectral im...

Machine Learning-Assisted, Dual-Channel CRISPR/Cas12a Biosensor-In-Microdroplet for Amplification-Free Nucleic Acid Detection for Food Authenticity Testing.

ACS nano
The development of novel detection technology for meat species authenticity is imperative. Here, we developed a machine learning-supported, dual-channel biosensor-in-microdroplet platform for meat species authenticity detection named CC-drop (RISPR/C...

Rapid detection of poultry meat quality using S-band to KU-band radio-frequency waves combined with machine learning-A proof of concept.

Journal of food science
Rapid changes in consumer preferences for high-quality animal-based protein have driven the poultry industry to identify non-invasive, in-line processing technologies for rapid detection of muscle meat quality defects. At production plants, technolog...